Working memory (WM), the cognitive entity that allows for temporary storage and manipulation of informa- tion, is crucial for much of what gives life subjective meaning, and enables an individual to participate in larger society. This includes following a conversation, finding a supermarket item, planning, driving, learning new skills?most anything that requires holding in mind information from long-term memory and/or sensory input for use requires WM. As a result, WM dysfunction has devastating effects, and regrettably, millions?individuals with schizophrenia, depression, ADHD, dementia, and more?experience varying degrees of WM impairment, which is almost totally treatment resistant. Given its role in neurocognitive health and disease, understanding the mechanisms of WM is imperative. Correspondingly, this project will explore in depth the circuit basis for WM. The prefrontal cortex (PFC) is known to be a primary orchestrator of WM, processing input from other brain regions for WM instantiation. In spatial working memory (SWM), a WM subdomain regularly studied across species, interactions of the PFC with the ventral hippocampus and mediodorsal nucleus of the thalamus (MD) are considered essential, with PFC-MD interactions undergirding neural maintenance of WM content and subsequent action selection. Notably, the PFC is quite heterogeneous, being composed of layers that differ both in their cellular composition and in their connectivity. Yet the possibility that these laminar subregions might uniquely contribute to the multifaceted ways in which the PFC empowers WM is only now being explored: recent studies suggest that superficial PFC layers support WM content maintenance, while deep PFC layers support post-maintenance action selection. This proposal expands upon these studies by using novel technology to explore cellular-resolution laminar representations in WM. Specifically, this proposal examines what WM content is encoded in the activity of individual cells vs. popula- tions in the different PFC layers (Aim 1) and assesses the dependence of these laminar WM representations on input from the MD (Aim 2). To do so, calcium imaging will be performed through microendoscopes in mice genetically and surgically specified to express calcium indicators in particular PFC layers. These mice will perform a trial-based delayed nonmatch to sample WM task in a custom-built, automated 8-armed radial maze, and for Aim 2 will have MD input to the PFC optogenetically silenced during behavior and imaging (to simulate the MD-PFC hypoconnectivity regularly observed in those with WM deficits). Finally, for rigorous mapping of behavior to neural activity, novel machine learning behavioral classification paradigms will be used. WM provides the cognitive building blocks for the very fabric of quotidian life?sustaining social relationships, maintaining a job, living independently, learning new things and more. Given such complexity, detailed interrogation of WM circuit mechanisms is required. Accordingly, this proposal uses emerging technologies to explore circuit mechanisms of both WM function and dysfunction, advancing pursuits of therapeutic innovation.